{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "\n",
    "df = pd.read_csv(\"random_people.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>name</th>\n",
       "      <th>surname</th>\n",
       "      <th>salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>William</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Black</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Green</td>\n",
       "      <td>5500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0     name  surname  salary\n",
       "0           0    Henry  Joneson    5000\n",
       "1           1   Albert  Goodman   10000\n",
       "2           2  William  Goodman   10000\n",
       "3           3     John  Joneson   10000\n",
       "4           4   Albert    Black   10000\n",
       "5           5    Henry  Joneson   12000\n",
       "6           6  Richard    Green    5500\n",
       "7           7    Henry  Joneson   11000\n",
       "8           8    Henry  Goodman   12000\n",
       "9           9   Albert  Joneson   11000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#start getting a feel of the data\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000    16\n",
       "12000     8\n",
       "11000     7\n",
       "9500      6\n",
       "5500      5\n",
       "13500     5\n",
       "5000      3\n",
       "Name: salary, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['salary'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['salary'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"salary_after_tax\"] = df[\"salary\"]*.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tax(s):\n",
    "    if s>=6000:\n",
    "        return s*.7\n",
    "    else:\n",
    "        return s*.85"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"salary_after_tax\"] = df[\"salary\"].apply(tax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>name</th>\n",
       "      <th>surname</th>\n",
       "      <th>salary</th>\n",
       "      <th>salary_after_tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>5000</td>\n",
       "      <td>4250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>William</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Black</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0     name  surname  salary  salary_after_tax\n",
       "0           0    Henry  Joneson    5000            4250.0\n",
       "1           1   Albert  Goodman   10000            7000.0\n",
       "2           2  William  Goodman   10000            7000.0\n",
       "3           3     John  Joneson   10000            7000.0\n",
       "4           4   Albert    Black   10000            7000.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_low = df[df[\"salary\"]<6000]\n",
    "df_high = df[df[\"salary\"]>=6000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10892.857142857143"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_high[\"salary\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_low= df.loc[df[\"salary\"]<6000,\"salary\"]\n",
    "df.loc[df[\"salary\"]<6000,\"salary_after_tax\"] = df_low*.85\n",
    "\n",
    "df_low= df.loc[df[\"salary\"]>=6000,\"salary\"]\n",
    "df.loc[df[\"salary\"]>=6000,\"salary_after_tax\"] = df_low*.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     4250.0\n",
       "6     4675.0\n",
       "14    4675.0\n",
       "17    4675.0\n",
       "21    4250.0\n",
       "32    4675.0\n",
       "33    4250.0\n",
       "37    4675.0\n",
       "Name: salary, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_low"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>name</th>\n",
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       "      <th>0</th>\n",
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       "      <td>Joneson</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>William</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Black</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Green</td>\n",
       "      <td>5500</td>\n",
       "      <td>4675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>William</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>John</td>\n",
       "      <td>White</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Black</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Green</td>\n",
       "      <td>5500</td>\n",
       "      <td>4675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Black</td>\n",
       "      <td>13500</td>\n",
       "      <td>9450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>Richard</td>\n",
       "      <td>White</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Black</td>\n",
       "      <td>5500</td>\n",
       "      <td>4675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Green</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>William</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>William</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>5000</td>\n",
       "      <td>4250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>John</td>\n",
       "      <td>Green</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>John</td>\n",
       "      <td>Black</td>\n",
       "      <td>13500</td>\n",
       "      <td>9450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Green</td>\n",
       "      <td>13500</td>\n",
       "      <td>9450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>William</td>\n",
       "      <td>Green</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Black</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>5500</td>\n",
       "      <td>4675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>5000</td>\n",
       "      <td>4250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Black</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35</td>\n",
       "      <td>John</td>\n",
       "      <td>White</td>\n",
       "      <td>13500</td>\n",
       "      <td>9450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>Henry</td>\n",
       "      <td>Green</td>\n",
       "      <td>11000</td>\n",
       "      <td>7700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37</td>\n",
       "      <td>John</td>\n",
       "      <td>Black</td>\n",
       "      <td>5500</td>\n",
       "      <td>4675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>William</td>\n",
       "      <td>Green</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Green</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>40</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>41</td>\n",
       "      <td>William</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>43</td>\n",
       "      <td>William</td>\n",
       "      <td>Black</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44</td>\n",
       "      <td>Albert</td>\n",
       "      <td>Black</td>\n",
       "      <td>12000</td>\n",
       "      <td>8400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45</td>\n",
       "      <td>John</td>\n",
       "      <td>Goodman</td>\n",
       "      <td>13500</td>\n",
       "      <td>9450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>46</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>47</td>\n",
       "      <td>John</td>\n",
       "      <td>Joneson</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>48</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Black</td>\n",
       "      <td>9500</td>\n",
       "      <td>6650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>49</td>\n",
       "      <td>Albert</td>\n",
       "      <td>White</td>\n",
       "      <td>10000</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0     name  surname  salary  salary_after_tax\n",
       "0            0    Henry  Joneson    5000            4250.0\n",
       "1            1   Albert  Goodman   10000            7000.0\n",
       "2            2  William  Goodman   10000            7000.0\n",
       "3            3     John  Joneson   10000            7000.0\n",
       "4            4   Albert    Black   10000            7000.0\n",
       "5            5    Henry  Joneson   12000            8400.0\n",
       "6            6  Richard    Green    5500            4675.0\n",
       "7            7    Henry  Joneson   11000            7700.0\n",
       "8            8    Henry  Goodman   12000            8400.0\n",
       "9            9   Albert  Joneson   11000            7700.0\n",
       "10          10  William  Joneson   10000            7000.0\n",
       "11          11     John    White   10000            7000.0\n",
       "12          12    Henry    Black   11000            7700.0\n",
       "13          13   Albert  Goodman   10000            7000.0\n",
       "14          14  Richard    Green    5500            4675.0\n",
       "15          15    Henry    Black   13500            9450.0\n",
       "16          16  Richard    White   11000            7700.0\n",
       "17          17   Albert    Black    5500            4675.0\n",
       "18          18    Henry    Green   10000            7000.0\n",
       "19          19   Albert  Joneson   11000            7700.0\n",
       "20          20  William  Goodman   12000            8400.0\n",
       "21          21  William  Goodman    5000            4250.0\n",
       "22          22     John    Green    9500            6650.0\n",
       "23          23     John    Black   13500            9450.0\n",
       "24          24  Richard    Green   13500            9450.0\n",
       "25          25    Henry  Joneson   12000            8400.0\n",
       "26          26    Henry  Goodman   10000            7000.0\n",
       "27          27     John  Joneson    9500            6650.0\n",
       "28          28    Henry  Goodman   11000            7700.0\n",
       "29          29  William    Green   12000            8400.0\n",
       "30          30    Henry  Goodman   10000            7000.0\n",
       "31          31  Richard    Black   10000            7000.0\n",
       "32          32  Richard  Joneson    5500            4675.0\n",
       "33          33  Richard  Joneson    5000            4250.0\n",
       "34          34    Henry    Black    9500            6650.0\n",
       "35          35     John    White   13500            9450.0\n",
       "36          36    Henry    Green   11000            7700.0\n",
       "37          37     John    Black    5500            4675.0\n",
       "38          38  William    Green   12000            8400.0\n",
       "39          39   Albert    Green   10000            7000.0\n",
       "40          40  Richard  Joneson    9500            6650.0\n",
       "41          41  William  Joneson   12000            8400.0\n",
       "42          42     John  Joneson   10000            7000.0\n",
       "43          43  William    Black   10000            7000.0\n",
       "44          44   Albert    Black   12000            8400.0\n",
       "45          45     John  Goodman   13500            9450.0\n",
       "46          46     John  Joneson   10000            7000.0\n",
       "47          47     John  Joneson    9500            6650.0\n",
       "48          48  Richard    Black    9500            6650.0\n",
       "49          49   Albert    White   10000            7000.0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(50)"
   ]
  }
 ],
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